Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Build apps faster and easier with high query performance, drivers, built-in tools and integrations supported by the largest graph community.
A Reactive architecture – from client applications and consumers through the network stack all the way to the database – allows for efficient use of compute, network bandwidth and minimizes latency for processing. A Reactive architecture also prevents overloading of clients by supporting backpressure to the data source.
Run complex queries over large graphs and slash request latencies from minutes (or hours) to milliseconds, with 10x less resources than RDBMS or NoSQL.
Cypher is the most widely used graph query language. Writing, understanding and maintaining Cypher queries is straightforward, simplifying application maintenance. At the same time, Cypher's building blocks are powerful enough for complex processing, reducing the number of roundtrips to the database. The top-notch query planner and execution engine utilize database information to optimally run statements for your needs.
MATCH (p:Product)-[:CATEGORY]->(l:ProductCategory)-[:PARENT*0..]->(:ProductCategory {name:"Dairy Products"})
RETURN p.name
SELECT p.ProductName
FROM Product AS p
JOIN ProductCategory pc ON (p.CategoryID = pc.CategoryID AND pc.CategoryName = "Dairy Products")
JOIN ProductCategory pc1 ON (p.CategoryID = pc1.CategoryID)
JOIN ProductCategory pc2 ON (pc1.ParentID = pc2.CategoryID AND pc2.CategoryName = "Dairy Products")
JOIN ProductCategory pc3 ON (p.CategoryID = pc3.CategoryID)
JOIN ProductCategory pc4 ON (pc3.ParentID = pc4.CategoryID)
JOIN ProductCategory pc5 ON (pc4.ParentID = pc5.CategoryID AND pc5.CategoryName = "Dairy Products");
With the property graph model, the data model you design on a whiteboard is the same as what you store in Neo4j and implement in your application. Even non-developers can continually understand the model and guide its evolution.
Neo4j officially supports drivers for .Net, Java, JavaScript, Go and Python. Higher level integrations like Spring Data Neo4j and the GRANDstack for GraphQL ease application development. AuraDB's UI comes with examples for these languages out of the box, customized for your databases.
Our community contributors thankfully provide drivers for PHP, Ruby, R, Erlang, Clojure, C/C++ and more.
Several tools, web-based and command line, allow easy migration of your Neo4j databases to AuraDB. In the AuraDB UI, simply upload local Neo4j .dump files via drag and drop.
Neo4j Browser is a developer UI that supports query building, retrieval, visualization, profiling, explaining, execution and result export. Interactive educational examples and resources are built in.
Neo4j Bloom™ is an easy-to-use graph exploration application for visually interacting with Neo4j graphs. Bloom is built for non-technical business users, as well as technical users, who want to demonstrate the power of graphs.
The monitoring dashboard features visual charts with continuous reporting of database performance, and resource utilization allows investigations of unexpected behavior and confirmation of ongoing operations.
APOC is a standard utility library with frequently used and powerful procedures and functions that can be used as building blocks within your Cypher queries. The larger part of APOC (apoc-core) is available out of the box in AuraDB, and automatically updated.
Available on AWS and Google Cloud in over 45 global cloud regions, deploy AuraDB in close proximity with your application in the region of your choice¹. AuraDB’s architecture ensures you can migrate to or across clouds seamlessly, and operate everywhere with consistency and performance. With AuraDB, you avoid cloud vendor lock-in with the freedom of choice.
¹Any region availability on Enterprise tier. See Pricing page for details.It's the easiest and fastest way to build graph applications in the cloud.
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